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Record W2742016598

The Effect of Training Strategies on the Performance of Trainees in the Kingdom of Saudi Arabia

2017· article· W2742016598 on OpenAlexaboutno aff

Bibliographic record

VenueRePEc: Research Papers in Economics · 2017
Typearticle
Language
FieldSocial Sciences
TopicSocioeconomic Development in MENA
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Human resourcesTraining (meteorology)Service (business)Customer serviceTraining and developmentHuman resource managementBusinessMedical educationPsychologyOperations managementManagementMarketingMedicineEngineeringGeography
DOInot available

Abstract

fetched live from OpenAlex

Staff training is one of the common concerns in thought and management application of modern management in the first quarter of the last century The awareness of the importance of the relationship between the training staff and their ability to invent new ways of doing business in these institutions is still limited As noted the trainees of the National Water Company NWC are inefficient in achieving customer service maintaining the facilities and repairing faults Thus this study aimed at identifying the effect of training strategies on the performance of trainees in NWC in Mecca city in the Kingdom of Saudi Arabia A total of 100 closed ended questionnaires were randomly distributed to employees such as managers heads of departments technicians and workers in NWC Of these only 85 questionnaires that were duly completed and analysed yielding a response rate of 85 Data were analysed statistically using SPSS software Version 19 0 Findings in Mecca show that almost 50 of the development of human resources was explained by the training strategy The two dimensions that were successfully predicted in the development of human resource were trainers and administrative and supervisory services The study comes out with several recommendations One of these recommendations is that NWC should obtain trainers from outside the company to improve the trainees expertise

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0300.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0020.006
Scholarly communication0.0000.000
Open science0.0040.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.361
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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